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yvesnormandin

CanLII MCP Server

search_canlii

Search the Canadian legal database for full-text judgments and documents by keyword, phrase, or case name.

Instructions

Search the CanLII Canadian legal database and return the full text of matching documents.

search_type values:

  • 'text': full-text search within document bodies — use for legal concepts, keywords, or phrases in judgments

  • 'name': search by case name, document title, file number, author, or citation — use for 'R v Oakes' or '2024 SCC 12'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query
max_resultsNoNumber of documents to fetch and return
search_typeNoWhich CanLII search box to usetext
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It discloses that the tool returns full text and explains the two search modes, but it does not mention limitations such as result ordering, pagination, rate limits, or explicitly confirm that the operation is read-only.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: one opening sentence defining the core function, followed by a clear, bullet-like breakdown of search_type values. Every sentence earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with a fully described schema, the description is almost complete. It specifies the return behavior (full text) and mode-specific use cases. Minor gaps include no mention of result format beyond 'full text' or error handling, but these are not critical given the schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers all parameters, so the baseline is 3. The description adds meaningful context beyond the schema, especially for search_type with concrete use cases and examples, making parameter selection more accurate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches the CanLII Canadian legal database and returns full-text documents. The explicit breakdown of search_type values with examples (legal concepts vs case names/citations) leaves no ambiguity about the tool's function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use guidance for each search_type mode ('use for legal concepts...' vs 'use for R v Oakes'), which helps the agent select the correct mode. However, it does not discuss alternatives to the tool itself or cases where the tool should not be used.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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